Statistical analysis:
Statistical analysis included comparing different parameters between
patients with pneumonia and COVID19 positive and those with COVID19
negative test results, using independent t-test for numerical variables
and chi-square for categorical variables. All significantly different
variables were entered in a forward stepwise binary logistic regression
analysis to select the best model. After selecting the best model. The
variable chosen in the last step was weighed using the odds ratios
calculated from the regression coefficient
(β) for each variable, the odds
ratios were multiplied by 0.125 to calculate a score for each variable
and the number was rounded to the nearest integer giving of scoring
system of 10 points. All study group patients were scored. The cutoff
point of the score was calculated using ROC analysis., and calculation
of sensitivity, specificity and accuracy was performed. Also, variables
associated with mortality in COVID19 positive were entered in a forward
binary logistic regression, which selected the best model and the odds
ratios was calculated for each variable using the regression coefficient
(β). Before entering the variables in the regression analysis
determination of the proper cutoff values of different contentious
variables was done using ROC analysis. patients Data were entered
checked and analyzed using SPSS for Windows version 16 (SPSS, Inc.
Chicago, IL, USA). For all the above mentioned statistical tests, the
threshold of significance is fixed at 5% level (P < 0.05).